1

Machine Learning Petroleum Engineer Jobs in California

As a Senior Machine Learning Engineer, you will design, build, and scale advanced software systems that automate Design for Manufacturing analysis, leveraging deep learning and computer vision ...

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...

Machine Learning Engineer

Sunnyvale, CA · On-site

$150.40 - $277.60/hr

Description Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and ...

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power ...

Machine Learning Engineer

San Francisco, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

Machine Learning Engineer

Mountain View, CA · On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI systems, collaborate with data engineering and research teams, and influence core decisions around ...

Machine Learning Engineer

Fremont, CA · On-site

$150K - $220K/yr

We are seeking a Machine Learning Engineer to join our team developing machine learning solutions for quality assurance and process monitoring in additive manufacturing. Working closely with process ...

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Machine Learning Engineer

Torrance, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do: * Research, develop and deploy cutting-edge deep learning ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Responsibilities : • Be an early member of a high-performing team of software engineers and machine learning researchers building a new human identity platform • Take ownership, be creative, and ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Showing results 41-60

Machine Learning Petroleum Engineer information

How does a machine learning petroleum engineer typically collaborate with geoscientists and drilling teams to optimize oil and gas production?

A Machine Learning Petroleum Engineer works closely with geoscientists and drilling teams by integrating data-driven models into exploration and production workflows. They analyze geological, seismic, and operational data to develop predictive algorithms that identify optimal drilling locations, forecast reservoir performance, and improve recovery rates. Regular collaboration involves translating complex data insights into actionable recommendations that guide drilling strategies and inform real-time decisions, ensuring all teams are aligned to maximize efficiency and safety. This multidisciplinary approach fosters continuous learning and innovation across teams.

What is the difference between Machine Learning Petroleum Engineer vs Reservoir Engineer?

AspectMachine Learning Petroleum EngineerReservoir Engineer
Required CredentialsBachelor's/Master's in Petroleum Engineering, Data Science, or related fields; knowledge of machine learningBachelor's/Master's in Petroleum Engineering or Geosciences; strong understanding of reservoir simulation
Work EnvironmentData analysis, modeling, software development in oil & gas companiesReservoir modeling, field development planning in oil & gas operations
Industry UsageApplying machine learning to optimize extraction, predict reservoir behaviorEstimating reservoir properties, managing production strategies

The Machine Learning Petroleum Engineer focuses on integrating data science and machine learning techniques to optimize oil extraction processes, while the Reservoir Engineer specializes in modeling and managing subsurface reservoirs to maximize recovery. Both roles are vital in the oil & gas industry but differ in their core skills and daily tasks.

What is a machine learning petroleum engineer?

A Machine Learning Petroleum Engineer is a specialist who combines expertise in petroleum engineering with machine learning and data science techniques. They use advanced algorithms and data analytics to optimize oil and gas exploration, drilling, production, and reservoir management. Their work helps improve decision-making, reduce operational costs, and increase efficiency by analyzing large datasets from various sources such as sensors, seismic data, and production logs. These professionals often work closely with geoscientists, data engineers, and other stakeholders in the energy sector.

What are the key skills and qualifications needed to thrive as a machine learning petroleum engineer?

To thrive as a Machine Learning Petroleum Engineer, you need a strong background in petroleum engineering, programming (such as Python or R), and applied machine learning, usually supported by a relevant engineering degree. Familiarity with data analysis platforms, machine learning frameworks (like TensorFlow or Scikit-learn), and petroleum industry software (such as Petrel or Eclipse) is essential. Strong analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for integrating technical insights with business goals. These competencies enable the effective application of data-driven solutions to optimize exploration, production, and operational efficiency in the energy sector.
What are popular job titles related to Machine Learning Petroleum Engineer jobs in California? For Machine Learning Petroleum Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Petroleum Engineer jobs in California look for? The top searched job categories for Machine Learning Petroleum Engineer jobs in California are:
What cities in California are hiring for Machine Learning Petroleum Engineer jobs? Cities in California with the most Machine Learning Petroleum Engineer job openings:

Full-time

Re-posted 11 days ago


Job description

THE OPPORTUNITY

Silvus is seeking a Machine Learning Engineer who will report to the R&D Director, Machine Learning on the R&D team.  The successful individual in this role will focus on applying machine learning and data-driven techniques to improve the performance, efficiency, and adaptability of Silvus' advanced MIMO radios and wireless networking systems.  This individual will work closely with experts in wireless communications, DSP, networking, and embedded systems to develop ML-driven features that solve real-world problems in dynamic and challenging RF environments.

This position is based at Silvus Technologies' headquarters in the heart of vibrant West Los Angeles, CA, and is on a hybrid schedule.  A minimum of 3 days onsite per week is expected. On-site days are Mondays, Wednesdays, and Thursdays.

The following is a list of at least some of the current essential job functions of the position. Management may assign or reassign duties and responsibilities at any time at its discretion.

 ROLE AND RESPONSIBILITIES

  • Research, design, and implement machine learning algorithms to enhance performance in wireless communication systems (e.g., link adaptation, interference mitigation, anomaly detection, spectrum sensing).
  • Analyze real-world RF datasets to extract insights and develop predictive models.
  • Develop software prototypes and integrate ML algorithms with Silvus' radio firmware and networking stack.
  • Collaborate with cross-functional teams to define ML use cases and evaluate the impact of deployed models.
  • Contribute to the design of data pipelines and infrastructure for training, testing, and validating models.
  • Participate in performance benchmarking and iterative improvement cycles.
  • Stay current with the latest Machine Learning research for wireless and embedded systems.
  • Perform other related duties of which the above are representative.

REQUIRED QUALIFICATIONS

  • Bachelor of Science degree in Electrical Engineering, Computer Science, Computer Engineering, or related field plus a minimum of 2 years of experience in machine learning, with demonstrated application to real-world problems; no experience required with an advance degree (MS or PhD)
  • Strong foundation in supervised and unsupervised learning and statistical modeling.
  • Experience with Python ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, etc.).
  • Exposure to MATLAB or C/C++ for signal processing algorithm development.
  • Must be a U.S. Citizen due to clients under U.S. government contracts.
  • All employment is contingent upon the successful clearance of a background check and drug test.

 PREFERRED KNOWLEDGE, SKILLS, AND ABILITIES

  • MS. or Ph.D. in Electrical Engineering, Computer Science, or a related field.
  • Demonstrated experience with RF signal classification, anomaly detection, or spectrum monitoring.
  • Proficiency in MATLAB or C/C++ for signal processing algorithm development.
  • Familiarity with wireless communication concepts (e.g., PHY/MAC layers, MIMO, OFDM, spectrum access).
  • Familiarity with embedded ML, real-time systems, or deploying ML on edge devices.
  • Background in adaptive modulation, beamforming, or cognitive radio techniques.
  • Experience working with wireless standards such as 3GPP, IEEE 802.11/15, or military waveforms.
  • Experience with GPU acceleration or model optimization for constrained environments.
  • Excellent communication and collaboration skills.

WORKING CONDITIONS AND PHYSICAL REQUIREMENTS

  • Office environment.
  • Outdoor environment for demos.
  • Occasional exposure to heat, cold, and allergens while performing tests or demonstrations in the field.
  • While performing the duties of this job, the employee is required to do the following:
    • Lift equipment up to 20 lbs. for the set-up of demonstrations and testing.
    • Perform bending and reaching movements to place items on lower and higher shelves.

#silvuscareers